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Effects of patient and imaging factors on small bowel motility scores derived from deep learning-based segmentation
Subin Heo1, Jihye Yun1, Dong Wook Kim2
1Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Objectives:
Small bowel motility can be quantified using cine MRI, but the influence of patient and imaging factors on motility scores remains unclear. This study evaluated whether patient and imaging factors affect motility scores derived from deep learning-based segmentation of cine MRI.
Materials And Methods:
Fifty-four patients (mean age 53.6 ± 16.4 years; 34 women) with chronic constipation or suspected colonic pseudo-obstruction who underwent cine MRI covering the entire small bowel between 2022 and 2023 were included. A deep learning algorithm was developed to segment small bowel regions, and motility was quantified with an optical flow-based algorithm, producing a motility score for each slice. Associations of motility scores with patient factors (age, sex, body mass index, symptoms, and bowel distension) and MRI slice-related factors (anatomical location, bowel area, and anteroposterior position) were analyzed using linear mixed models.
Results:
Deep learning-based small bowel segmentation achieved a mean volumetric Dice similarity coefficient of 75.4 ± 18.9%, with a manual correction time of 26.5 ± 13.5 s. Median motility scores per patient ranged from 26.4 to 64.4, with an interquartile range of 3.1-26.6. Multivariable analysis revealed that MRI slice-related factors, including anatomical location with mixed ileum and jejunum (β = -4.9; p = 0.01, compared with ileum dominant), bowel area (first order β = -0.2, p < 0.001; second order β = 5.7 × 10-4, p < 0.001), and anteroposterior position (first order β = -51.5, p < 0.001; second order β = 28.8, p = 0.004) were significantly associated with motility scores. Patient factors showed no association with motility scores.
Conclusion:
Small bowel motility scores were significantly associated with MRI slice-related factors. Determining global motility without adjusting for these factors may be limited.
Key Points:
Question Global small bowel motility can be quantified from cine MRI; however, the confounding factors affecting motility scores remain unclear. Findings Motility scores were significantly influenced by MRI slice-related factors, including anatomical location, bowel area, and anteroposterior position. Clinical relevance Adjusting for slice-related factors is essential for accurate interpretation of small bowel motility scores on cine MRI.
Insights
Small bowel motility scores from cine MRI are influenced by imaging slice factors, not patient characteristics. Accurate interpretation requires adjusting for anatomical location, bowel area, and position.
Area of Science:
- Gastroenterology
- Medical Imaging
- Artificial Intelligence
Background:
- Quantifying small bowel motility using cine MRI is possible.
- However, the impact of patient and imaging variables on motility scores is not well understood.
Purpose of the Study:
- To investigate whether patient and imaging factors influence small bowel motility scores derived from deep learning-based segmentation of cine MRI.
Main Methods:
- A deep learning algorithm segmented small bowel regions in cine MRI scans from 54 patients.
- Motility scores were calculated using an optical flow-based algorithm.
- Linear mixed models analyzed associations between scores and patient/imaging factors.
Main Results:
- Deep learning segmentation achieved a 75.4% Dice similarity coefficient.
- Motility scores were significantly associated with MRI slice factors: anatomical location, bowel area, and anteroposterior position.
- No significant association was found between patient factors and motility scores.
Conclusions:
- Small bowel motility scores are significantly influenced by MRI slice-related factors.
- Accurate interpretation of global small bowel motility from cine MRI necessitates adjustments for these slice-specific factors.
